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Title:Sistem za uvrstitev spletnih virov na podlagi spletnega grafa : magistrsko delo
Authors:ID Kutoš, Leon (Author)
ID Lukač, Niko (Mentor) More about this mentor... New window
ID Jesenko, David (Comentor)
Files:.pdf MAG_Kutos_Leon_2022.pdf (1,57 MB)
MD5: 1344080CDD0CFBA061A5B93CC987B144
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Magistrsko delo se navezuje na razvoj sistema za uvrščanje spletnih strani, kjer uporabimo spletni pajek, algoritem TF-IDF ter algoritma PageRank in TrustRank. Razvili smo sistem, ki je sestavljen iz pridobivanja podatkov s pomočjo spletnega pajka, grupiranje po vsebinski tematiki ter računanje PageRank in TrustRank vrednosti posameznih spletnih strani. Sistem smo testirali na dvema realnima in dvema sintetičnima scenarijema. V vseh primerih je sistem uspešno ustvaril spletni graf in spletne strani uvrstil po njihovi pomembnosti. Predlagan sistem omogoča učinkovit pregled nad spletnimi povezavami ter uvrstitev spletnih strani glede njihove pomembnosti.
Keywords:spletni graf, PageRank, TrustRank, spletne aplikacije
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[L. Kutoš]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (X, 36 f.))
PID:20.500.12556/DKUM-82581 New window
UDC:004.774/.775(043.2)
COBISS.SI-ID:131640323 New window
Publication date in DKUM:21.10.2022
Views:670
Downloads:100
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:25.08.2022

Secondary language

Language:English
Title:Web resource ranking system based on a webgraph
Abstract:The master's thesis is related to the development of a system for ranking websites, where we use the web crawler, the TF-IDF algorithm, and the PageRank and TrustRank algorithm. We have developed a system that consists of obtaining data with the help of a web crawler, grouping by content topic and calculating the PageRank and TrustRank values of individual web pages. We tested the system on two real and two synthetic scenarios. In all cases, the system successfully created a web graph and ranked the web pages according to their importance. The proposed system enables an efficient review of web links and ranks the web pages based on their importance.
Keywords:webgraph, PageRank, TrustRank, websites


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